Machine Learning, Human Factors and Security Analysis for the Remote Command of Driving: An MCity Pilot
Both human drivers and autonomous vehicles are now able to drive relatively well in ‘typical’ (frequently- encountered) settings, but fail in exceptional cases. Worse, these exceptional cases often arise suddenly, leaving human drivers with a few seconds at best to react—exactly the setting that people perform worst in. This work proposes methods for leveraging groups of remote operators to provide assistance on- demand. Unlike prior work, we introduce collective workflows that enable groups of operators to significantly outperform any of the constituent individuals on control and correction tasks. We propose to develop a software platform for MCity that enables a group of remote operators to command the autonomous test vehicles at MCity. A pilot study will be conducted at the Mcity Test Facility.
- Record URL:
Language
- English
Project
- Status: Completed
- Funding: $178,371
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Contract Numbers:
69A3551747105
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Center for Connected and Automated Transportation
University of Michigan Transportation Research Institute
Ann Arbor, MI United States 48109 -
Project Managers:
Tucker-Thomas, Dawn
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Performing Organizations:
University of Michigan Transportation Research Institute
2901 Baxter Road
Ann Arbor, Michigan United States 48109 Ann Arbor, MI United States -
Principal Investigators:
Hampshire, Robert
Lasecki, Walter
Bao, Shan
- Start Date: 20180901
- Expected Completion Date: 20200831
- Actual Completion Date: 20200831
- USDOT Program: University Transportation Centers Program
- Subprogram: Research
Subject/Index Terms
- TRT Terms: Human factors; Mathematical models; Operations
- Identifier Terms: Naturalistic Driving Study Database
- Subject Areas: Data and Information Technology; Research; Transportation (General);
Filing Info
- Accession Number: 01665948
- Record Type: Research project
- Source Agency: Center for Connected and Automated Transportation
- Contract Numbers: 69A3551747105
- Files: UTC, RIP
- Created Date: Apr 12 2018 12:18PM